Estimation of wind turbine rotor power coefficient using RMP model

Gum Tae Son, Hee Jin Lee, Jung Wook Park

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

This paper presents an estimation of the rotor power coefficient (C p) curve, which is useful for pitch angle control of a wind turbine system. The Cp curve is affected by several factors such as the structure of a wind turbine, surrounding environment in which the wind turbine built, and its method of control, etc. Therefore, it is necessary to estimate this curve in real-time using direct measurements from the generator and wind turbine. To achieve the optimal estimation for the Cp curve, the reduced multivariate polynomial (RMP) model is applied because it can be basically represented in a polynomial form. Unlike general neural network algorithms, the RMP model avoids a training process. This characteristic makes it possible to apply to the real-time estimation in a practical situation. Also, the first-order partial derivatives of the Cp curve are easily computed by using the RMP model. This derivative information can be effectively used to maximize turbine output power by a proper pitch angle control. The simulation results show that the proposed RMP model provides a good estimation performance in a fast and effective manner.

Original languageEnglish
Title of host publication2009 IEEE Industry Applications Society Annual Meeting
DOIs
Publication statusPublished - 2009 Dec 1
Event2009 IEEE Industry Applications Society Annual Meeting - Houston, TX, United States
Duration: 2008 Oct 42008 Oct 8

Publication series

NameConference Record - IAS Annual Meeting (IEEE Industry Applications Society)
ISSN (Print)0197-2618

Other

Other2009 IEEE Industry Applications Society Annual Meeting
CountryUnited States
CityHouston, TX
Period08/10/408/10/8

Fingerprint

Wind turbines
Rotors
Derivatives
Turbines
Polynomials
Neural networks
Statistical Models

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

Cite this

Son, G. T., Lee, H. J., & Park, J. W. (2009). Estimation of wind turbine rotor power coefficient using RMP model. In 2009 IEEE Industry Applications Society Annual Meeting [5324837] (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)). https://doi.org/10.1109/IAS.2009.5324837
Son, Gum Tae ; Lee, Hee Jin ; Park, Jung Wook. / Estimation of wind turbine rotor power coefficient using RMP model. 2009 IEEE Industry Applications Society Annual Meeting. 2009. (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)).
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Son, GT, Lee, HJ & Park, JW 2009, Estimation of wind turbine rotor power coefficient using RMP model. in 2009 IEEE Industry Applications Society Annual Meeting., 5324837, Conference Record - IAS Annual Meeting (IEEE Industry Applications Society), 2009 IEEE Industry Applications Society Annual Meeting, Houston, TX, United States, 08/10/4. https://doi.org/10.1109/IAS.2009.5324837

Estimation of wind turbine rotor power coefficient using RMP model. / Son, Gum Tae; Lee, Hee Jin; Park, Jung Wook.

2009 IEEE Industry Applications Society Annual Meeting. 2009. 5324837 (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - This paper presents an estimation of the rotor power coefficient (C p) curve, which is useful for pitch angle control of a wind turbine system. The Cp curve is affected by several factors such as the structure of a wind turbine, surrounding environment in which the wind turbine built, and its method of control, etc. Therefore, it is necessary to estimate this curve in real-time using direct measurements from the generator and wind turbine. To achieve the optimal estimation for the Cp curve, the reduced multivariate polynomial (RMP) model is applied because it can be basically represented in a polynomial form. Unlike general neural network algorithms, the RMP model avoids a training process. This characteristic makes it possible to apply to the real-time estimation in a practical situation. Also, the first-order partial derivatives of the Cp curve are easily computed by using the RMP model. This derivative information can be effectively used to maximize turbine output power by a proper pitch angle control. The simulation results show that the proposed RMP model provides a good estimation performance in a fast and effective manner.

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Son GT, Lee HJ, Park JW. Estimation of wind turbine rotor power coefficient using RMP model. In 2009 IEEE Industry Applications Society Annual Meeting. 2009. 5324837. (Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)). https://doi.org/10.1109/IAS.2009.5324837